Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton

Key message

Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton.

Abstract

A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.

     

GWAS for plant growth stages and yield components in spring wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) harvested in three regions of Kazakhstan

Background

Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS.

Results

Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits.

Conclusions

Field evaluation of foreign germplasm revealed its poor yield performance in Northern Kazakhstan, which is the main wheat growing region in the country. However, it was found that EU and CIMMYT germplasm has high breeding potential to improve yield performance in Central and Southern regions. The use of Principal Coordinate analysis clearly separated the panel into three distinct groups according to their breeding origin. GWAS based on use of the TASSEL 5.0 package allowed the identification of 114 MTAs for twelve agronomic traits. The study identifies a network of key genes for improvement of yield productivity in wheat growing regions of Kazakhstan.

     

Genome-wide association mapping reveals a rich genetic architecture of stripe rust resistance loci in emmer wheat (<Emphasis Type="Italic">Triticum turgidum</Emphasis> ssp. <Emphasis Type="Italic">dicoccum</Emphasis>)

Key message

SNP-based genome scanning in worldwide domesticated emmer germplasm showed high genetic diversity, rapid linkage disequilibrium decay and 51 loci for stripe rust resistance, a large proportion of which were novel.

Abstract

Cultivated emmer wheat (Triticum turgidum ssp. dicoccum), one of the oldest domesticated crops in the world, is a potentially rich reservoir of variation for improvement of resistance/tolerance to biotic and abiotic stresses in wheat. Resistance to stripe rust (Puccinia striiformis f. sp. tritici) in emmer wheat has been under-investigated. Here, we employed genome-wide association (GWAS) mapping with a mixed linear model to dissect effective stripe rust resistance loci in a worldwide collection of 176 cultivated emmer wheat accessions. Adult plants were tested in six environments and seedlings were evaluated with five races from the United States and one from Italy under greenhouse conditions. Five accessions were resistant across all experiments. The panel was genotyped with the wheat 90,000 Illumina iSelect single nucleotide polymorphism (SNP) array and 5106 polymorphic SNP markers with mapped positions were obtained. A high level of genetic diversity and fast linkage disequilibrium decay were observed. In total, we identified 14 loci associated with field resistance in multiple environments. Thirty-seven loci were significantly associated with all-stage (seedling) resistance and six of them were effective against multiple races. Of the 51 total loci, 29 were mapped distantly from previously reported stripe rust resistance genes or quantitative trait loci and represent newly discovered resistance loci. Our results suggest that GWAS is an effective method for characterizing genes in cultivated emmer wheat and confirm that emmer wheat is a rich source of stripe rust resistance loci that can be used for wheat improvement.

     

An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding

Key message

The innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding.

Abstract

The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was used for genetic characterization, candidate gene prediction, and genomic selection for optimal crosses in the germplasm population.

     

Linkage disequilibrium and genome-wide association analysis for anthocyanin pigmentation and fruit color in eggplant

Background

The genome-wide association (GWA) approach represents an alternative to biparental linkage mapping for determining the genetic basis of trait variation. Both approaches rely on recombination to re-arrange the genome, and seek to establish correlations between phenotype and genotype. The major advantages of GWA lie in being able to sample a much wider range of the phenotypic and genotypic variation present, in being able to exploit multiple rounds of historical recombination in many different lineages and to include multiple accessions of direct relevance to crop improvement.

Results

A 191 accessions eggplant (Solanum melongena L.) association panel, comprising a mixture of breeding lines, old varieties and landrace selections originating from Asia and the Mediterranean Basin, was SNP genotyped and scored for anthocyanin pigmentation and fruit color at two locations over two years. The panel formed two major clusters, reflecting geographical provenance and fruit type. The global level of linkage disequilibrium was 3.4 cM. A mixed linear model appeared to be the most appropriate for GWA. A set of 56 SNP locus/phenotype associations was identified and the genomic regions harboring these loci were distributed over nine of the 12 eggplant chromosomes. The associations were compared with the location of known QTL for the same traits.

Conclusion

The GWA mapping approach was effective in validating a number of established QTL and, thanks to the wide diversity captured by the panel, was able to detect a series of novel marker/trait associations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-896) contains supplementary material, which is available to authorized users.     

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

Key message

Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction.

Abstract

In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom^TM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.

     

QTL mapping of fruit mineral contents provides new chances for molecular breeding of tomato nutritional traits

Key message

Agronomical characterization of a RIL population for fruit mineral contents allowed for the identification of QTL controlling these fruit quality traits, flanked by co-dominant markers useful for marker-assisted breeding.

Abstract

Tomato quality is a multi-variant attribute directly depending on fruit chemical composition, which in turn determines the benefits of tomato consumption for human health. Commercially available tomato varieties possess limited variability in fruit quality traits. Wild species, such as Solanum pimpinellifolium, could provide different nutritional advantages and can be used for tomato breeding to improve overall fruit quality. Determining the genetic basis of the inheritance of all the traits that contribute to tomato fruit quality will increase the efficiency of the breeding program necessary to take advantage of the wild species variability. A high-density linkage map has been constructed from a recombinant inbred line (RIL) population derived from a cross between tomato Solanum lycopersicum and the wild-relative species S. pimpinellifolium. The RIL population was evaluated for fruit mineral contents during three consecutive growing seasons. The data obtained allowed for the identification of main QTL and novel epistatic interaction among QTL controlling fruit mineral contents on the basis of a multiple-environment analysis. Most of the QTL were flanked by candidate genes providing valuable information for both tomato breeding for new varieties with novel nutritional properties and the starting point to identify the genes underlying these QTL, which will help to reveal the genetic basis of tomato fruit nutritional properties.

     

Multi-environment QTL mapping reveals genetic architecture of fruit cracking in a tomato RIL <Emphasis Type="Italic">Solanum lycopersicum</Emphasis> × <Emphasis Type="Italic">S. pimpinellifolium</Emphasis> population

Key message

QTL and codominant genetic markers for fruit cracking have been identified in a tomato genetic map derived from a RIL population, providing molecular tools for marker-assisted breeding of this trait.

Abstract

In tomato, as well as in other fleshy fruits, one of the main disorders that widely limit quality and production is fruit cracking or splitting of the epidermis that is observed on the fruit skin and flesh at any stage of fruit growth and maturation. To elucidate the genetic basis of fruit cracking, a quantitative trait loci (QTL) analysis was conducted in a recombinant inbred line (RIL) population derived from a cross between tomato (Solanum lycopersicum) and the wild-relative species S. pimpinellifolium. The RIL population was evaluated for fruit cracking during three consecutive growing seasons. Construction of a high-density linkage map based on codominant markers, covering more than 1000 cM of the whole genome, led to the identification of both main and epistatic QTL controlling fruit cracking on the basis of a single-environment as well as multiple-environment analysis. This information will enhance molecular breeding for novel cracking resistant varieties and simultaneously assist the identification of genes underlying these QTL, helping to reveal the genetic basis of fruit cracking in tomato.

     

Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt

Key message

High-throughput genotyping of Swiss bread wheat and spelt accessions revealed differences in their gene pools and identified bread wheat landraces that were not used in breeding.

Abstract

Genebanks play a pivotal role in preserving the genetic diversity present among old landraces and wild progenitors of modern crops and they represent sources of agriculturally important genes that were lost during domestication and in modern breeding. However, undesirable genes that negatively affect crop performance are often co-introduced when landraces and wild crop progenitors are crossed with elite cultivars, which often limit the use of genebank material in modern breeding programs. A detailed genetic characterization is an important prerequisite to solve this problem and to make genebank material more accessible to breeding. Here, we genotyped 502 bread wheat and 293 spelt accessions held in the Swiss National Genebank using a 15K wheat SNP array. The material included both spring and winter wheats and consisted of old landraces and modern cultivars. Genome- and sub-genome-wide analyses revealed that spelt and bread wheat form two distinct gene pools. In addition, we identified bread wheat landraces that were genetically distinct from modern cultivars. Such accessions were possibly missed in the early Swiss wheat breeding program and are promising targets for the identification of novel genes. The genetic information obtained in this study is appropriate to perform genome-wide association studies, which will facilitate the identification and transfer of agriculturally important genes from the genebank into modern cultivars through marker-assisted selection.

     

A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton

Key message

A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield.

Abstract

Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.

     

From the editor’s desk

Improving cotton fibre quality is a major breeding goal for Upland cotton in China. To investigate the genetic mechanisms of fibre quality, a diverse panel of 403 Upland cotton accessions was grown, and the fibre quality traits were measured in six different environments. Genotyping was performed with genomewide simple sequence repeats. A total of 201 markers were polymorphic and generated 394 allele loci, and 403 accessions were arranged into two subgroups using Structure software. Of the marker loci, 18.94% showed significant linkage disequilibrium (\(P< 0.05\)). A mixed linear model in association mapping showed that 51 associations were significant between 39 polymorphic loci and five fibre quality traits, according to best linear unbiased prediction, and in at least three of six environments. Of the 39 associated marker loci, 12 were coincident with previous studies. There were 41 typical accessions identified as containing favourable allele loci related to fibre quality traits. The identified favourable QTL alleles and typical accessions for fibre quality are excellent genetic resources for future cotton breeding in China.     

Genetic diversity,population structure,and linkage disequilibrium of elite and local apple accessions from Belgium using the IRSC array

The identification of molecular markers associated with economic and quality traits will help improve breeding for new apple (Malus × domestica Borkh.) cultivars. Tools such as the 8K apple SNP array developed by the RosBREED consortium allow for high-throughput genotyping of SNP polymorphisms within collections. However, genetic characterization and the identification of population stratification and kinship within germplasm collections is a fundamental prerequisite for identifying robust marker–trait associations. In this study, a collection of apple germplasm originally developed for plant architectural studies and consisting of both non-commercial/local and elite accessions was genotyped using the 8K apple SNP array to identify cryptic relationships between accessions, to analyze population structure and to calculate the linkage disequilibrium (LD). A total of nine pairs of synonyms and several triploids accessions were identified within the 130 accessions genotyped. In addition, most of the known parent-child relations were confirmed, and several putative, previously unknown parent-child relations were identified among the local accessions. No clear subgroups could be identified although some separation between local and elite accessions was evident. The study of LD showed a rapid decay in our collection, indicating that a larger number of SNPs is necessary to perform whole genome association mapping. Finally, an association mapping effort for architectural traits was carried out on a small number of accessions to estimate the feasibility of this approach.     

Bayesian QTL mapping using genome-wide SSR markers and segregating population derived from a cross of two commercial F<Subscript>1</Subscript> hybrids of tomato

Key message

Using newly developed euchromatin-derived genomic SSR markers and a flexible Bayesian mapping method, 13 significant agricultural QTLs were identified in a segregating population derived from a four-way cross of tomato.

Abstract

So far, many QTL mapping studies in tomato have been performed for progeny obtained from crosses between two genetically distant parents, e.g., domesticated tomatoes and wild relatives. However, QTL information of quantitative traits related to yield (e.g., flower or fruit number, and total or average weight of fruits) in such intercross populations would be of limited use for breeding commercial tomato cultivars because individuals in the populations have specific genetic backgrounds underlying extremely different phenotypes between the parents such as large fruit in domesticated tomatoes and small fruit in wild relatives, which may not be reflective of the genetic variation in tomato breeding populations. In this study, we constructed F₂ population derived from a cross between two commercial F₁ cultivars in tomato to extract QTL information practical for tomato breeding. This cross corresponded to a four-way cross, because the four parental lines of the two F₁ cultivars were considered to be the founders. We developed 2510 new expressed sequence tag (EST)-based (euchromatin-derived) genomic SSR markers and selected 262 markers from these new SSR markers and publicly available SSR markers to construct a linkage map. QTL analysis for ten agricultural traits of tomato was performed based on the phenotypes and marker genotypes of F₂ plants using a flexible Bayesian method. As results, 13 QTL regions were detected for six traits by the Bayesian method developed in this study.

     

Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats

Key message

Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation.

Abstract

Increases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (<?1 cM). QTL identified and validated in this study provide useful information for the improvement of fall-sown spring wheats under full and limited irrigation.

     

Genome-wide investigation of genetic changes during modern breeding of Brassica napus

Key message

Considerable genome variation had been incorporated within rapeseed breeding programs over past decades.

Abstract

In past decades, there have been substantial changes in phenotypic properties of rapeseed as a result of extensive breeding effort. Uncovering the underlying patterns of allelic variation in the context of genome organisation would provide knowledge to guide future genetic improvement. We assessed genome-wide genetic changes, including population structure, genetic relatedness, the extent of linkage disequilibrium, nucleotide diversity and genetic differentiation based on F _ST outlier detection, for a panel of 472 Brassica napus inbred accessions using a 60 k Brassica Infinium^® SNP array. We found genetic diversity varied in different sub-groups. Moreover, the genetic diversity increased from 1950 to 1980 and then remained at a similar level in China and Europe. We also found ~6–10 % genomic regions revealed high F _ST values. Some QTLs previously associated with important agronomic traits overlapped with these regions. Overall, the B. napus C genome was found to have more high F _ST signals than the A genome, and we concluded that the C genome may contribute more valuable alleles to generate elite traits. The results of this study indicate that considerable genome variation had been incorporated within rapeseed breeding programs over past decades. These results also contribute to understanding the impact of rapeseed improvement on available genome variation and the potential for dissecting complex agronomic traits.     

Genome-wide association mapping for seedling and field resistance to <Emphasis Type="Italic">Puccinia striiformis</Emphasis> f. sp. <Emphasis Type="Italic">tritici</Emphasis> in elite durum wheat

Key message

Genome-wide association analysis in tetraploid wheat revealed novel and diverse loci for seedling and field resistance to stripe rust in elite spring durum wheat accessions from worldwide.

Abstract

Improving resistance to stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major objective for wheat breeding. To identify effective stripe rust resistance loci, a genome-wide association study (GWAS) was conducted using 232 elite durum wheat (Triticum turgidum ssp. durum) lines from worldwide breeding programs. Genotyping with the 90 K iSelect wheat single nucleotide polymorphism (SNP) array resulted in 11,635 markers distributed across the genome. Response to stripe rust infection at the seedling stage revealed resistant and susceptible accessions present in rather balanced frequencies for the six tested races, with a higher frequency of susceptible responses to United States races as compared to Italian races (61.1 vs. 43.1% of susceptible accessions). Resistance at the seedling stage only partially explained adult plant resistance, which was found to be more frequent with 67.7% of accessions resistant across six nurseries in the United States. GWAS identified 82 loci associated with seedling stripe rust resistance, five of which were significant at the false discovery rate adjusted P value <0.1 and 11 loci were detected for the field response at the adult plant stages in at least two environments. Notably, Yrdurum-1BS.1 showed the largest effect for both seedling and field resistance, and is therefore considered as a major locus for resistance in tetraploid wheat. Our GWAS study is the first of its kind for stripe rust resistance in tetraploid wheat and provides an overview of resistance in elite germplasm and reports new loci that can be used in breeding resistant cultivars.

     

Identification and validation of genomic regions influencing kernel zinc and iron in maize

Key message

Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize.

Abstract

Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world’s poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P?≤?5.03?×?10^?05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P?≤?1?×?10^?03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P?≤?0.01, R²?≥?0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

     

Detection of favorable alleles for yield and yield components by association mapping in upland cotton

Association mapping based on linkage disequilibrium provides a promising tool for dissecting the genetic basis underlying complex traits. To reveal the genetic variations of yield and yield components traits in upland cotton, 403 upland cotton accessions were collected and analyzed by 560 genome-wide simple sequence repeats (SSRs). A diverse panel consisting of 403 upland cotton accessions was grown in six different environments, and the yield and yield component traits were measured, and 560 SSR markers covering the whole genome were mapped. Association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Favorable alleles and typical accessions for yield traits were identified. A total of 201 markers were polymorphic, revealing 394 alleles. The average gene diversity and polymorphism information content were 0.556 and 0.483, respectively. Based on a population structure analysis, 403 accessions were divided into two subgroups. A mixed linear model analysis of the association mapping detected 43 marker loci according to the best linear unbiased prediction and in at least three of the six environments(??lgP?>?1.30, P?<?0.05). Among the 43 associated markers, five were associated with more than two traits simultaneously and nine were coincident with those identified previously. Based on phenotypic effects, favorable alleles and typical accessions that contained the elite allele loci related to yield traits were identified and are widely used in practical breeding. This study detected favorable quantitative trait loci’s alleles and typical accessions for yield traits, these are excellent genetic resources for future high-yield breeding by marker-assisted selection in upland cotton in China.     

The western Mediterranean region provided the founder population of domesticated narrow-leafed lupin

Key message

This study revealed that the western Mediterranean provided the founder population for domesticated narrow-leafed lupin and that genetic diversity decreased significantly during narrow-leafed lupin domestication.

Abstract

The evolutionary history of plants during domestication profoundly shaped the genome structure and genetic diversity of today’s crops. Advances in next-generation sequencing technologies allow unprecedented opportunities to understand genome evolution in minor crops, which constitute the majority of plant domestications. A diverse set of 231 wild and domesticated narrow-leafed lupin (Lupinus angustifolius L.) accessions were subjected to genotyping-by-sequencing using diversity arrays technology. Phylogenetic, genome-wide divergence and linkage disequilibrium analyses were applied to identify the founder population of domesticated narrow-leafed lupin and the genome-wide effect of domestication on its genome. We found wild western Mediterranean population as the founder of domesticated narrow-leafed lupin. Domestication was associated with an almost threefold reduction in genome diversity in domesticated accessions compared to their wild relatives. Selective sweep analysis identified no significant footprints of selection around domestication loci. A genome-wide association study identified single nucleotide polymorphism markers associated with pod dehiscence. This new understanding of the genomic consequences of narrow-leafed lupin domestication along with molecular marker tools developed here will assist plant breeders more effectively access wild genetic diversity for crop improvement.

     

Unlocking new alleles for leaf rust resistance in the Vavilov wheat collection

Key message

Thirteen potentially new leaf rust resistance loci were identified in a Vavilov wheat diversity panel. We demonstrated the potential of allele stacking to strengthen resistance against this important pathogen.

Abstract

Leaf rust (LR) caused by Puccinia triticina is an important disease of wheat (Triticum aestivum L.), and the deployment of genetically resistant cultivars is the most viable strategy to minimise yield losses. In this study, we evaluated a diversity panel of 295 bread wheat accessions from the N. I. Vavilov Institute of Plant Genetic Resources (St Petersburg, Russia) for LR resistance and performed genome-wide association studies (GWAS) using 10,748 polymorphic DArT-seq markers. The diversity panel was evaluated at seedling and adult plant growth stages using three P. triticina pathotypes prevalent in Australia. GWAS was applied to 11 phenotypic data sets which identified a total of 52 significant marker–trait associations representing 31 quantitative trait loci (QTL). Among them, 29 QTL were associated with adult plant resistance (APR). Of the 31 QTL, 13 were considered potentially new loci, whereas 4 co-located with previously catalogued Lr genes and 14 aligned to regions reported in other GWAS and genomic prediction studies. One seedling LR resistance QTL located on chromosome 3A showed pronounced levels of linkage disequilibrium among markers (r ² = 0.7), suggested a high allelic fixation. Subsequent haplotype analysis for this region found seven haplotype variants, of which two were strongly associated with LR resistance at seedling stage. Similarly, analysis of an APR QTL on chromosome 7B revealed 22 variants, of which 4 were associated with resistance at the adult plant stage. Furthermore, most of the tested lines in the diversity panel carried 10 or more combined resistance-associated marker alleles, highlighting the potential of allele stacking for long-lasting resistance.